The task of generating and updating known routes and trails of human activity is usually performed manually, by at least three different groups, including (a) city, state, and national governmental organizations, such as the USGS, (b) large international companies, or (c) crowd-sourced efforts, such as OpenStreetMap.org. All of these manual approaches rely on explicit agents (such as survey workers, drivers of cars capable of tracking GPS data, or OSM volunteers). These agents must (1) take the time to traverse paths and trails for the purposes of mapping, (2) be diligent enough to transfer their records into a central database, and (3) be sure to record their paths with sufficient accuracy. When the agent fails even on a small scale in any of his or her duties, the resulting maps are less than ideal.
The current manual approaches to generating and updating maps suffer several shortcomings. In some cases, a new path that should be included on a map will not be identified until an agent is deployed to record the path. Consequently, a path may go unrecorded for days, weeks, months, or longer. As another problem, an organization designated to map a region may resist the mapping of “unsanctioned” paths even if such paths are frequently used. For example, an organization may not wish to map backcountry trails if such trails are not sanctioned by a local municipality. This may be due to any of various reasons, such as limited resources that will only allow for the mapping of official trails, or not wanting to promote the use of a particular path (e.g., a dangerous path) by making it more widely known. As another issue with current systems, the accuracy of path representation typically relies on a single agent who is often employed by or paid by the mapping entity.
Accordingly, it would be advantageous to provide a system for obtaining mapping data for use in mapping new paths and also improving upon maps for existing paths. It would also be advantageous if the mapping data could be more quickly obtained and with a greater degree of accuracy. It would also be advantageous if the mapping data could be collected with relatively little expense.